{"id":"https://openalex.org/W2987190284","doi":"https://doi.org/10.1145/3357384.3357962","title":"Imbalance Rectification in Deep Logistic Regression for Multi-Label Image Classification Using Random Noise Samples","display_name":"Imbalance Rectification in Deep Logistic Regression for Multi-Label Image Classification Using Random Noise Samples","publication_year":2019,"publication_date":"2019-11-03","ids":{"openalex":"https://openalex.org/W2987190284","doi":"https://doi.org/10.1145/3357384.3357962","mag":"2987190284"},"language":"en","primary_location":{"id":"doi:10.1145/3357384.3357962","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3357962","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047171802","display_name":"Wenjin Yan","orcid":"https://orcid.org/0000-0003-0947-7836"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjin Yan","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039670436","display_name":"Ruixuan Li","orcid":"https://orcid.org/0000-0002-7791-5511"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruixuan Li","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384838","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-9515-076X"},"institutions":[{"id":"https://openalex.org/I4210094759","display_name":"Fujitsu (United States)","ror":"https://ror.org/0073whr05","country_code":"US","type":"company","lineage":["https://openalex.org/I2252096349","https://openalex.org/I4210094759"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Fujitsu Laboratories of America, Sunnyvale, CA, USA","Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Laboratories of America, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210094759"]},{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432137","display_name":"Yuhua Li","orcid":"https://orcid.org/0000-0002-1846-4941"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhua Li","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100766570","display_name":"Jinyang Wang","orcid":"https://orcid.org/0000-0003-4372-6920"},"institutions":[{"id":"https://openalex.org/I4210094759","display_name":"Fujitsu (United States)","ror":"https://ror.org/0073whr05","country_code":"US","type":"company","lineage":["https://openalex.org/I2252096349","https://openalex.org/I4210094759"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jinyang Wang","raw_affiliation_strings":["Fujitsu Laboratories of America, Sunnyvale, CA, USA","Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujitsu Laboratories of America, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210094759"]},{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693197","display_name":"Pan Zhou","orcid":"https://orcid.org/0000-0002-8629-4622"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Zhou","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083995138","display_name":"Xiwu Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiwu Gu","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1131","last_page":"1140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7275587916374207},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6409885883331299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6070600152015686},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5896955728530884},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5707786083221436},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5271755456924438},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4793039858341217},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4355064332485199},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4140913486480713},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3950933814048767},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.37508708238601685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3305385112762451},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2990454435348511}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7275587916374207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6409885883331299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6070600152015686},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5896955728530884},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5707786083221436},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5271755456924438},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4793039858341217},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4355064332485199},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4140913486480713},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3950933814048767},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37508708238601685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3305385112762451},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2990454435348511},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3357384.3357962","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3357962","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1965365402","https://openalex.org/W1965895350","https://openalex.org/W2007972815","https://openalex.org/W2108598243","https://openalex.org/W2118978333","https://openalex.org/W2146241755","https://openalex.org/W2161381512","https://openalex.org/W2166704235","https://openalex.org/W2167464971","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2471768434","https://openalex.org/W2761434131","https://openalex.org/W2775447965","https://openalex.org/W2963351448","https://openalex.org/W2963875806","https://openalex.org/W2963951032","https://openalex.org/W3106250896"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W2129863591","https://openalex.org/W1596769710","https://openalex.org/W2923497059","https://openalex.org/W2978363435","https://openalex.org/W4321636575","https://openalex.org/W1986418932","https://openalex.org/W2357796999","https://openalex.org/W2005234362","https://openalex.org/W1997235926"],"abstract_inverted_index":{"Logistic":[0],"regression":[1],"(LR)":[2],"is":[3,52],"the":[4,23,120,140,146,152],"most":[5],"commonly":[6],"used":[7],"loss":[8,121],"function":[9],"in":[10,26,119],"multi-label":[11],"image":[12],"classification.":[13],"However,":[14],"it":[15],"suffers":[16],"from":[17],"class":[18,58,125],"imbalance":[19,65],"problem":[20],"caused":[21],"by":[22],"huge":[24],"difference":[25],"quantity":[27],"between":[28,36],"positive":[29],"and":[30,60,107,123,137,145,155],"negative":[31],"samples":[32,47],"as":[33,35],"well":[34],"different":[37],"classes.":[38],"First,":[39],"we":[40,76],"find":[41],"that":[42],"feeding":[43],"randomly":[44],"generated":[45],"noise":[46,72],"into":[48],"an":[49,53,63,78],"LR":[50,154],"classifier":[51],"effective":[54],"way":[55],"to":[56,113],"detect":[57],"imbalances,":[59],"further":[61],"define":[62],"informative":[64],"metric":[66],"named":[67],"inference":[68,86,117,143],"tendency":[69,108,118,144],"based":[70,82],"on":[71,133],"sample":[73],"analysis.":[74],"Second,":[75],"design":[77],"efficient":[79],"moving":[80],"average":[81],"method":[83],"for":[84],"calculating":[85],"tendency,":[87],"which":[88],"can":[89],"be":[90],"easily":[91],"done":[92],"during":[93],"training":[94],"with":[95,131],"negligible":[96],"overhead.":[97],"Third,":[98],"two":[99],"novel":[100],"rectification":[101],"methods":[102],"called":[103],"extremum":[104],"shift":[105],"(ES)":[106],"constraint":[109],"(TC)":[110],"are":[111],"designed":[112],"offset":[114],"or":[115],"constrain":[116],"function,":[122],"mitigate":[124],"imbalances":[126],"significantly.":[127],"Finally,":[128],"comparative":[129],"experiments":[130],"Resnet":[132],"Microsoft":[134],"COCO,":[135],"NUS-WIDE":[136],"DeepFashion":[138],"demonstrate":[139],"effectiveness":[141],"of":[142,148],"superiority":[147],"our":[149],"approach":[150],"over":[151],"baseline":[153],"several":[156],"state-of-the-art":[157],"alternatives.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
